Power battery module side seam welding monitoring system based on digital twinning

Abstract

The invention relates to a power battery module side seam welding monitoring system based on digital twinning, and belongs to the technical field of battery welding, the power battery module side seam welding monitoring system comprises a data acquisition module used for acquiring welding data in real time; the selection mapping module is used for acquiring three-dimensional models corresponding to the side seam welding equipment and the welding product, and mapping the welding data and the corresponding three-dimensional models; the model construction module is used for constructing a digital twin model based on the three-dimensional model and the welding data corresponding to the three-dimensional model; the data early warning module is used for comparing the welding data in the digital twin model with preset data and generating warning information under the condition that the welding data does not conform to the preset data; and the report generation module is used for generating a welding report based on the alarm information and the three-dimensional model corresponding to the alarm information. According to the method, the welding process and the equipment operation state are observed in real time through the digital twinborn model, the alarm information is generated under the condition that abnormity is found, welding defects are corrected in time, and then defective products are reduced.

Description

Technical Field

[0001] The present application relates to the technical field of battery welding, and in particular to a power battery module side seam welding monitoring system based on digital twins. Background Art

[0002] In the existing power battery production process, welding is an extremely important link in the module assembly stage. Since power battery production is almost irreversible, the technical requirements for welding quality are quite high.

[0003] The side seam welding method for the power battery module is to install the welding gun on the sixth axis of the robot to weld four seams. The existing technology has the following problems: (1) In order to prevent welding slag from splashing outside the welding area during welding, protective devices are installed around the welding area to seal it, which makes it difficult for personnel outside to observe the equipment operation status and product production process, resulting in a visual blind spot during welding; (2) When making product changes, experimental adjustments to equipment parameters may cause equipment or product collision damage, resulting in more defective products and increasing overall costs. Summary of the invention

[0004] In order to solve the above problems, the present application provides a power battery module side seam welding monitoring system based on digital twin.

[0005] In the first aspect, the present application provides a power battery module side seam welding monitoring system based on digital twin, which adopts the following technical solutions: A power battery module side seam welding monitoring system based on digital twin, comprising: A data acquisition module, used for acquiring welding data in real time, wherein the welding data includes side seam welding equipment data and welding product data; Selecting a mapping module to obtain a three-dimensional model corresponding to the side seam welding equipment and the welding product, and mapping the welding data with the corresponding three-dimensional model; A model building module, used to build a digital twin model based on the three-dimensional model and welding data corresponding to the three-dimensional model; A data warning module, used to compare the welding data in the digital twin model with preset data, and generate an alarm message when the welding data does not conform to the preset data; A report generation module is used to generate a welding report based on the alarm information and the three-dimensional model corresponding to the alarm information.

[0006] By adopting the above technical solution, users can observe the welding process and equipment operation status in real time through the digital twin model without directly contacting the welding area, thereby solving the visual blind spot problem caused by the closure of the protective device in the traditional welding method. In addition, the digital twin model can monitor the welding process in real time and generate alarm information in time when an abnormality is found, so that personnel can take timely measures to correct welding defects and reduce the production of defective products.

[0007] Optionally, the system further includes a data processing module, wherein the data processing module is used to: After the welding data is acquired, the welding data is preprocessed to obtain data to be analyzed, wherein the preprocessing includes data deduplication and data standardization; Check whether there are wrong values ​​and / or missing values ​​in the data to be analyzed; If so, the wrong value and / or missing value is corrected and supplemented based on the historical welding data to obtain the data to be used; The data to be used is sent to the selection mapping module.

[0008] By adopting the above technical solution, the welding data can be preprocessed and corrected to ensure the consistency of the welding data in time, space and different dimensions, providing a reliable foundation for subsequent data analysis and model building; and by preprocessing and correcting the welding data, the accuracy of the digital twin model can be improved.

[0009] Optionally, the correcting and supplementing the wrong value and / or missing value based on the historical welding data includes: Obtain the data type of the wrong value and / or missing value; Acquire historical welding data corresponding to the data type; Sorting the historical welding data according to time to obtain a data sequence; Marking the positions of the wrong values ​​and / or missing values ​​in the data sequence to obtain marked positions; Selecting historical welding data adjacent to the marked position; Perform linear difference calculation based on the selected historical welding data to obtain correction data for the wrong value and / or missing value; The erroneous values ​​and / or missing values ​​are corrected and supplemented based on the correction data.

[0010] By adopting the above technical solution and utilizing historical welding data, erroneous values ​​and missing values ​​are effectively corrected and supplemented, thereby ensuring the integrity of the welding data set and avoiding analysis deviations and misjudgments caused by missing or incorrect data.

[0011] Optionally, the welding data includes a welding image, and the system further includes a correction module, wherein the correction module is specifically used for: Acquire a welding image and a three-dimensional model corresponding to the welding image, wherein the welding image includes a side seam welding equipment image and a welding product image; The welding image and the three-dimensional model corresponding to the welding image are combined into a processing group; For the same treatment group: Determining a reference position of the welding image on the three-dimensional model; intercepting a reference image corresponding to the reference position; comparing the reference image with the welding image; In the case where the reference image does not match the welding image, determining that there is an error between the side seam welding equipment data in the actual scene and the three-dimensional model corresponding to the welding product; determining an error value based on the reference image and the welding image; A movement path of the three-dimensional model is generated based on the error value.

[0012] By adopting the above technical solution, the deviation between the welding image and the three-dimensional model can be detected in real time through the correction module, and timely adjustments can be made to ensure the synchronization between the digital twin model and the actual scene.

[0013] Optionally, the system further includes an image processing module, and the image processing module is specifically used to: After acquiring the welding image, the clarity of the welding image is adjusted to obtain a clear image; The clear image is used as a welding image for comparison with a reference image.

[0014] By adopting the above technical solution, the accuracy of synchronization analysis is improved.

[0015] Optionally, generating a movement path of the three-dimensional model based on the error value includes: The three-dimensional model corresponding to the error value is used as the three-dimensional model to be moved; Determine a starting point and an end point of the three-dimensional model to be moved, and connect the starting point and the end point to form a route to be selected; Moving the three-dimensional model to be moved on the selected route, and determining whether the three-dimensional model to be moved collides with other three-dimensional models; If yes, then obtain the coordinate information of the collision point; Adjust the coordinate information based on a preset adjustment strategy to obtain adjusted coordinates; The candidate route is adjusted based on the adjusted coordinates to obtain the moving path.

[0016] By adopting the above technical solution, the three-dimensional model is adjusted through the error value to improve the synchronization between the real scene and the digital twin model.

[0017] Optionally, the system further includes a model rendering module, and the model rendering module is specifically used to: Obtain images to be analyzed from all directions of the side seam welding equipment and welded products in the actual scene; Extracting element features from the image to be analyzed, wherein the element features include texture features; generating a rendered sticker based on the texture features; Obtaining images to be processed in all directions of the three-dimensional model; Determining an adjustment ratio of the texture feature based on the image to be analyzed and an image to be processed corresponding to the image to be analyzed; Adjusting the rendered sticker based on the adjustment ratio; Stick the adjusted rendering sticker to the corresponding position of the corresponding 3D model.

[0018] By adopting the above technical solution, the model rendering module accurately extracts texture features and generates rendering stickers, and affixes the rendering stickers to the corresponding three-dimensional model, making the three-dimensional model of welding equipment and welding products more realistic.

[0019] Optionally, the system further includes a debugging module, and the debugging module is specifically used to: Get the user's debugging information; generating a moving path of the three-dimensional model based on the debugging information; Moving the three-dimensional model based on the moving path; Performing collision detection on the moved three-dimensional model, and generating an adjustment path based on the collision information when the moved three-dimensional model collides; The three-dimensional model is adjusted based on the adjustment path, and the adjustment data is displayed.

[0020] By adopting the above technical solution, when product changes or welding parameter changes are required, the welding process of the product is simulated through the digital twin model and collision detection is performed. Once a collision occurs, the module will immediately generate an adjustment path to avoid potential risks in the actual welding process.

[0021] Optionally, the report generation module is specifically used to: Obtaining a three-dimensional model corresponding to the warning information; Adjusting the three-dimensional model to the problem area corresponding to the alarm information to obtain an adjusted three-dimensional model; Capturing a display image of the adjusted three-dimensional model; generating a model link of the adjusted three-dimensional model; A welding report is generated based on the model link, the display image and the warning information.

[0022] By adopting the above technical solution, through intercepting and adjusting the three-dimensional model and display image, the user can quickly adjust to the corresponding problem area in the digital twin model according to the welding report, thereby improving the efficiency of problem solving.

[0023] Optionally, before adjusting the three-dimensional model to the problem area corresponding to the warning information, the method further includes: Classifying the welding data to obtain data types; Performing a first number on each of the data types; Performing a second numbering on the display area of ​​each of the three-dimensional models; The data type is associated with the corresponding display area based on the first number and the second number.

[0024] By adopting the above technical solution, the first number and the second number are associated, so that it is convenient to quickly locate the corresponding display area of ​​the corresponding three-dimensional model according to the alarm information, thereby improving the efficiency of generating welding reports. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a structural block diagram of a power battery module side seam welding monitoring system based on digital twin in the example of this application. DETAILED DESCRIPTION

[0026] The present application is further described in detail below in conjunction with the accompanying drawings.

[0027] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, those skilled in the art may make modifications to the present embodiment without any creative contribution as needed, but such modifications are protected by the patent law as long as they are within the scope of the claims of the present application.

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0029] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0030] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0031] The embodiment of the present application provides a power battery module side seam welding monitoring system based on digital twins, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a desktop computer, etc., but is not limited thereto.

[0032] like Figure 1 As shown, a power battery module side seam welding monitoring system based on digital twins includes: A data acquisition module 100 is used to acquire welding data in real time, the welding data including side seam welding equipment data and welding product data; In this embodiment, the side seam welding equipment data and the welding product data include welding data of multiple stages in the welding process, wherein the stages include but are not limited to welding initialization, process and end stages; the side seam welding equipment data include but are not limited to welding robot position coordinates, angle posture data, current and voltage, end plate clamping mechanism, welding speed, welding materials, temperature operation and status data and welding robot motion image, and the welding product data include but are not limited to CCD detection positioning image, side seam welding image and product image, wherein the equipment for collecting the side seam welding equipment data and welding product data includes but is not limited to sensors and cameras.

[0033] Among them, the power battery module side seam welding monitoring system based on digital twin also includes a data processing module and an image processing module. When the data acquisition module 100 obtains welding data, the welding data is input into the data processing module and the image processing module for processing.

[0034] The image processing module is specifically used for: adjusting the clarity of the welding image after acquiring the welding image to obtain a clear image; and using the clear image as a welding image for comparison with a reference image.

[0035] In this embodiment, when the image processing module obtains the CCD detection positioning image, the side seam welding image and the product image, the CCD detection positioning image, the side seam welding image and the product image are input into the image processing module.

[0036] The image processing module processes the CCD detection positioning image, the side seam welding image and the product image in the following ways, but not limited to: (1) Remove noise from CCD detection positioning images, side seam welding images, and product images through filtering algorithms or deep learning models to improve the clarity of CCD detection positioning images, side seam welding images, and product images.

[0037] (2) Contrast enhancement: Adjust the contrast of the CCD detection positioning image, side seam welding image and product image to make the details in the CCD detection positioning image, side seam welding image and product image clearer.

[0038] (3) Binarization processing: For some application scenarios, converting the CCD detection positioning image, side seam welding image and product image into binary images (black and white images) can simplify the subsequent processing steps.

[0039] (4) Histogram equalization: By adjusting the histogram distribution of the CCD detection positioning image, the side seam welding image and the product image, the contrast and brightness of the CCD detection positioning image, the side seam welding image and the product image are enhanced.

[0040] (5) Image super-resolution technology: By interpolating and reconstructing low-resolution CCD detection positioning images, side seam welding images and product images, high-resolution CCD detection positioning images, side seam welding images and product images are generated; the super-resolution SRCNN model based on deep learning can learn the mapping relationship between low-resolution images and high-resolution images, thereby generating high-quality images.

[0041] (6) Use a deeper network structure and increase the number of network layers to improve the model's feature extraction capabilities. Use more complex feature extraction methods: such as residual blocks and attention mechanisms in convolutional neural networks (CNNs), which can more effectively extract image features.

[0042] The data processing module is specifically used to: pre-process the welding data after acquiring the welding data to obtain the data to be analyzed, the pre-processing includes data deduplication and data standardization; query whether there are wrong values ​​and / or missing values ​​in the data to be analyzed; if so, correct and supplement the wrong values ​​and / or missing values ​​based on historical welding data to obtain the data to be used; send the data to be used to the selection mapping module.

[0043] In this embodiment, the welding data processed by the data processing module and the image processing module, that is, the data to be analyzed, is stored in a database, and the sensitive data is encrypted.

[0044] Among them, querying whether there are wrong values ​​and / or missing values ​​in the data to be analyzed includes: sorting the data to be analyzed in chronological order, dividing two adjacent welding data into a data group, calculating the data difference between the two welding data in each data group, comparing the data difference with a preset difference, and when the data difference does not meet the preset difference, determining that the data group has wrong values, taking the data group with wrong values ​​as the first problem data group, obtaining two data groups adjacent to the first problem data group, taking the data group whose data difference between the two adjacent data groups does not meet the preset difference as the second problem data group, and determining the wrong values ​​based on the first problem data group and the second problem data group.

[0045] For example, each data group is numbered. In this embodiment, data group 1, data group 2 and data group 3 are taken as examples for explanation. The data to be analyzed in data group 1 are a and b; the data to be analyzed in data group 2 are b and c; the data to be analyzed in data group 3 are c and d; when data group 2 and data group 3 are the first problem data group and the second problem data group, data c is a wrong value; when data group 1 and data group 2 are the first problem data group and the second problem data group, data b is a wrong value; when data group 2 is the first problem data group and data group 1 and data group 3 are the second problem data group, data b and data c are wrong values.

[0046] Among them, the preset difference can be determined based on historical welding data, such as calculating the difference between two adjacent welding data in the historical welding data, removing the maximum value and the minimum value, dividing the remaining difference into two groups according to the data size, calculating the average value of the difference in each group, and combining the two average values ​​into a difference interval. The difference interval is the preset difference mentioned above. The preset difference can also be set as needed, and there is no specific limitation on this.

[0047] In this embodiment, when the data to be analyzed is obtained, it is queried whether each time corresponds to a data to be analyzed. When there is no data to be analyzed at a certain time, it is determined that there is a missing value at the time.

[0048] When there are data types with wrong values ​​and / or missing values, the wrong values ​​and / or missing values ​​need to be corrected and supplemented.

[0049] Specifically, the data type of the wrong value and / or missing value is obtained; the historical welding data corresponding to the data type is obtained; the historical welding data is sorted according to time to obtain a data sequence; the position of the wrong value and / or missing value in the data sequence is marked to obtain the marked position; the historical welding data adjacent to the marked position is selected; a linear difference calculation is performed based on the selected historical welding data to obtain corrected data for the wrong value and / or missing value; and the wrong value and / or missing value is corrected and supplemented based on the corrected data.

[0050] In this embodiment, when there are wrong values ​​and / or missing values, the data type of the wrong values ​​and / or missing values ​​is determined, and the historical welding data of the corresponding data type is sorted by time to obtain a data sequence, wherein the data type includes but is not limited to side seam welding equipment, welding products, welding robot position coordinates, angle posture data, current and voltage, end plate clamping mechanism, welding speed, welding materials, weld width, weld depth and weld fusion, and the missing values ​​and / or wrong values ​​are marked in the corresponding data sequence to obtain the corresponding marking position, wherein color marking and other marking methods can be used, and there is no specific limitation on this.

[0051] In this embodiment, historical welding data adjacent to the marked position is obtained, and linear difference calculation is performed based on the adjacent historical welding data to obtain correction data for missing values ​​and / or wrong values.

[0052] Selecting a mapping module 200 for obtaining a three-dimensional model corresponding to the side seam welding equipment and the welding product, and mapping the welding data with the corresponding three-dimensional model; In this embodiment, it is queried whether there are three-dimensional models corresponding to the welding equipment and the welding products in the model library. If so, the corresponding three-dimensional models are extracted. If not, high-precision three-dimensional scanning, photogrammetry and other technical means are used to scan and extract the geometric shape, texture information, and material properties of the welding equipment and the welding products, so as to generate a corresponding three-dimensional model one to one.

[0053] In this embodiment, each three-dimensional model is mapped to the corresponding welding data to construct a digital twin model.

[0054] A model building module 300 is used to build a digital twin model based on the three-dimensional model and welding data corresponding to the three-dimensional model; In this embodiment, the three-dimensional model and the welding data corresponding to the three-dimensional model are imported into a digital twin platform or simulation software to generate a data twin model to simulate the side seam welding process of the power battery module.

[0055] The digital twin-based power battery module side seam welding monitoring system also includes a correction module, which is specifically used to: obtain a welding image and a three-dimensional model corresponding to the welding image, the welding image includes a side seam welding equipment image and a welding product image; form a processing group with the welding image and the three-dimensional model corresponding to the welding image; for the same processing group: determine the reference position of the welding image in the three-dimensional model; intercept the reference image corresponding to the reference position; compare the reference image with the welding image; when the reference image does not match the welding image, determine that there is an error between the side seam welding equipment data in the actual scene and the three-dimensional model corresponding to the welding product; determine the error value based on the reference image and the welding image; and generate a moving path of the three-dimensional model based on the error value.

[0056] Among them, generating a moving path of a three-dimensional model based on an error value includes: taking the three-dimensional model corresponding to the error value as the three-dimensional model to be moved; determining the starting point and the end point of the three-dimensional model to be moved, connecting the starting point and the end point to form a selected route; moving the three-dimensional model to be moved along the selected route, and determining whether the three-dimensional model to be moved collides with other three-dimensional models; if so, obtaining coordinate information of the collision point; adjusting the coordinate information based on a preset adjustment strategy to obtain adjusted coordinates; adjusting the selected route based on the adjusted coordinates to obtain a moving path.

[0057] In this embodiment, the welding image in this step refers to the position and posture image of the side seam welding equipment. The reference image and the welding image are input into the trained neural network model to obtain an error value, wherein the error value is the distance that the three-dimensional model to be moved needs to move; in this embodiment, a three-dimensional coordinate system of the digital twin model is constructed, and the starting point and end point of the three-dimensional model to be moved are determined in the three-dimensional coordinate system, wherein the starting point is the current position, and the end point is the expected position, which is a position that matches the real scene. The starting point and the end point are connected to form a preliminary route to be selected.

[0058] When the three-dimensional model to be moved moves along the selected route, a collision detection algorithm, such as space division, hierarchical bounding box, etc., is used to check whether the three-dimensional model to be moved will collide with other three-dimensional models or obstacles; if a collision is detected, the coordinate information of the collision point is obtained, and the distance without collision is determined according to the coordinate information of the collision point and the coordinate information of the three-dimensional model where the collision occurs, such as obtaining the coordinate information of the edge point of the three-dimensional model where the collision occurs, calculating the distance to be moved according to the coordinate information of the collision point and the coordinate information of the edge point, and determining the adjusted coordinates according to the distance to be moved, thereby adjusting the selected route according to the adjusted coordinates to obtain a moving path, that is, a collision-free moving path, wherein the adjustment strategy includes but is not limited to changing the moving direction, adjusting the moving speed, bypassing obstacles, etc. In this embodiment, a collision is considered to have occurred when the distance between the two three-dimensional models is less than 10 cm.

[0059] The digital twin-based power battery module side seam welding monitoring system also includes a model rendering module, which is specifically used to: obtain images to be analyzed in various directions of side seam welding equipment and welding products in actual scenes; extract element features in the images to be analyzed, wherein the element features include texture features; generate rendering stickers based on texture features; obtain images to be processed in various directions of the three-dimensional model; determine the adjustment ratio of texture features based on the images to be analyzed and the processed images corresponding to the images to be analyzed; adjust the rendering stickers based on the adjustment ratio; and fit the adjusted rendering stickers to the corresponding positions of the corresponding three-dimensional models.

[0060] In this embodiment, a high-resolution industrial camera is used to photograph the side seam welding equipment and the welding product from all directions to obtain an image to be analyzed, and the image to be analyzed is preprocessed, such as denoising, contrast enhancement, etc., to ensure that the image quality meets the analysis requirements; advanced image recognition technology, such as deep learning or computer vision algorithm, is used to extract key texture features from the preprocessed image to be analyzed; the extracted features are screened to retain features that have a significant impact on the welding process or can accurately reflect the surface properties of the object; corresponding rendering stickers are generated based on the extracted texture features; through image registration or alignment algorithms, it is ensured that the image to be analyzed is consistent with the image to be processed in terms of viewing angle, resolution and scale, so as to perform subsequent feature matching and adjustment; and the feature matching algorithm is used to match the texture features in the image to be analyzed with the corresponding features in the image to be processed.

[0061] Adjusting the ratio is used to adjust the size, shape and position of the rendering sticker to ensure that it fits perfectly with the surface of the 3D model; according to the calculated adjustment ratio, the rendering sticker is adjusted accordingly; the adjusted rendering sticker is accurately fitted to the corresponding position of the 3D model.

[0062] You can also extract the core elements of the reference image, such as the light source position, shadow part, model part, exposure, matte, color, etc., and integrate these core elements into the rendered sticker to make the digital twin model more in line with the real scene.

[0063] The data warning module 400 is used to compare the welding data in the digital twin model with the preset data, and generate an alarm message when the welding data does not meet the preset data; In this embodiment, the welding product data can be compared with the preset data to determine whether the welding product meets the standards, such as weld width, weld depth, and weld fusion. When it does not meet the standards, an alarm message is generated; similarly, the various welding parameters of the side seam welding equipment are compared with the preset data to determine whether the data of the side seam welding equipment meets the standards, such as temperature, speed, angle posture data, current voltage, etc.

[0064] The report generation module 500 is used to generate a welding report based on the alarm information and the three-dimensional model corresponding to the alarm information.

[0065] The report generation module is specifically used to: obtain the three-dimensional model corresponding to the alarm information; adjust the three-dimensional model to the problem area corresponding to the alarm information to obtain the adjusted three-dimensional model; intercept the display image of the adjusted three-dimensional model; generate a model link of the adjusted three-dimensional model; and generate a welding report based on the model link, the display image and the alarm information.

[0066] Before adjusting the three-dimensional model to the problem area corresponding to the alarm information, it also includes: classifying the welding data to obtain the data type; giving each data type a first number; giving each display area of ​​the three-dimensional model a second number; and associating the data type with the corresponding display area based on the first number and the second number.

[0067] In this embodiment, each adjustment parameter has a corresponding display area in the three-dimensional model. For example, the angle posture data of the welding equipment, the weld width and weld depth of the welding product all have corresponding display areas in the corresponding three-dimensional model. The data type is associated with the corresponding display area through the first number and the second number, which facilitates quick positioning of the display area corresponding to the three-dimensional model according to the welding data, and facilitates user observation.

[0068] Among them, the data types include but are not limited to side seam welding equipment, welding products, welding robot position coordinates, angle posture data, current and voltage, end plate clamping mechanism, welding speed, welding materials, weld width, weld depth and weld fusion.

[0069] In this embodiment, alarm information is obtained, and the alarm information includes abnormal welding data. The data type of the welding data is used to quickly locate the problem area of ​​the corresponding three-dimensional model, that is, the display area.

[0070] In this embodiment, an image capture tool is used to capture a display image from the adjusted three-dimensional model and generate a unique link or URL for the adjusted three-dimensional model; a welding report is generated through the model link, display image and alarm information.

[0071] When the user queries the alarm information, he can directly switch to the problem area of ​​the 3D model corresponding to the alarm information through the link in the welding report, which is convenient for observation.

[0072] The digital twin-based power battery module side seam welding monitoring system also includes a debugging module, which is specifically used to: obtain the user's debugging information; generate a moving path of the three-dimensional model based on the debugging information; move the three-dimensional model based on the moving path; perform collision detection on the moved three-dimensional model, and in the event of a collision of the moved three-dimensional model, generate an adjustment path based on the collision information; adjust the three-dimensional model based on the adjustment path, and display the adjustment data.

[0073] In this embodiment, when the product or welding data changes, the welding process of the product is modeled through the digital twin model, and the user inputs debugging information, which includes but is not limited to the starting position, target position, moving speed, acceleration and welding product size of the three-dimensional model.

[0074] The debugging module generates the moving path of the three-dimensional model using advanced path planning algorithms such as the A-star algorithm, Dijkstra algorithm, and RRT algorithm according to the debugging information input by the user; optimizes the generated moving path to reduce the moving time, improve the smoothness of the path, or avoid unnecessary obstacles; uses the control interface of the three-dimensional model to convert the generated moving path into specific moving instructions and send them to the three-dimensional model for execution; during the movement of the three-dimensional model, monitors its position and status in real time to ensure that the movement process proceeds as expected. During the movement of the three-dimensional model, collision detection algorithms such as bounding boxes and space segmentation are used to detect in real time whether the model collides with other three-dimensional models.

[0075] If a collision is detected, record the collision information such as the position, direction, and speed of the collision point; based on the collision information, use path adjustment algorithms such as re-planning the path and detour strategies to generate a new adjustment path to avoid the collision; convert the generated adjustment path into specific adjustment instructions and send them to the 3D model for execution; record key data in the adjustment process, such as the position, speed, acceleration, etc. before and after the adjustment, and display the corresponding data so that the user can adjust the input debugging information according to the displayed data, so as to apply it to actual production.

[0076] The terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or also includes elements inherent to such process, method, article, or apparatus.

[0077] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of application involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned application concept. For example, the above features are replaced with (but not limited to) technical features with similar functions applied in the present application.

Claims

1. A power battery module side seam welding monitoring system based on digital twin, characterized in that: include: A data acquisition module, used for acquiring welding data in real time, wherein the welding data includes side seam welding equipment data and welding product data; Selecting a mapping module to obtain a three-dimensional model corresponding to the side seam welding equipment and the welding product, and mapping the welding data with the corresponding three-dimensional model; A model building module, used to build a digital twin model based on the three-dimensional model and welding data corresponding to the three-dimensional model; A data warning module, used to compare the welding data in the digital twin model with preset data, and generate an alarm message when the welding data does not conform to the preset data; A report generation module, used for generating a welding report based on the alarm information and the three-dimensional model corresponding to the alarm information; The system further comprises a data processing module, wherein the data processing module is used to: After the welding data is acquired, the welding data is preprocessed to obtain data to be analyzed, wherein the preprocessing includes data deduplication and data standardization; Check whether there are wrong values ​​and / or missing values ​​in the data to be analyzed; If so, the wrong value and / or missing value is corrected and supplemented based on the historical welding data to obtain the data to be used; The data to be used is sent to the selection mapping module.

2. According to a digital twin-based power battery module side seam welding monitoring system according to claim 1, the correction and supplementation of the wrong value and / or missing value based on historical welding data includes: Obtain the data type of the wrong value and / or missing value; Acquire historical welding data corresponding to the data type; Sorting the historical welding data according to time to obtain a data sequence; Marking the positions of the wrong values ​​and / or missing values ​​in the data sequence to obtain marked positions; Selecting historical welding data adjacent to the marked position; Perform linear difference calculation based on the selected historical welding data to obtain correction data for the wrong value and / or missing value; The erroneous values ​​and / or missing values ​​are corrected and supplemented based on the correction data.

3. According to claim 1, a power battery module side seam welding monitoring system based on digital twin is characterized in that: The welding data includes a welding image, and the system further includes a correction module, which is specifically used for: Acquire a welding image and a three-dimensional model corresponding to the welding image, wherein the welding image includes a side seam welding equipment image and a welding product image; The welding image and the three-dimensional model corresponding to the welding image are combined into a processing group; For the same treatment group: Determining a reference position of the welding image on the three-dimensional model; intercepting a reference image corresponding to the reference position; comparing the reference image with the welding image; In the case where the reference image does not match the welding image, determining that there is an error between the side seam welding equipment data in the actual scene and the three-dimensional model corresponding to the welding product; determining an error value based on the reference image and the welding image; A movement path of the three-dimensional model is generated based on the error value.

4. According to claim 3, a power battery module side seam welding monitoring system based on digital twin is characterized in that: The system further includes an image processing module, which is specifically used for: After acquiring the welding image, the clarity of the welding image is adjusted to obtain a clear image; The clear image is used as a welding image for comparison with a reference image.

5. According to claim 3, a power battery module side seam welding monitoring system based on digital twin is characterized in that: The step of generating a moving path of the three-dimensional model based on the error value comprises: The three-dimensional model corresponding to the error value is used as the three-dimensional model to be moved; Determine a starting point and an end point of the three-dimensional model to be moved, and connect the starting point and the end point to form a route to be selected; Moving the three-dimensional model to be moved on the selected route, and determining whether the three-dimensional model to be moved collides with other three-dimensional models; If yes, then obtain the coordinate information of the collision point; Adjust the coordinate information based on a preset adjustment strategy to obtain adjusted coordinates; The candidate route is adjusted based on the adjusted coordinates to obtain the moving path.

6. A power battery module side seam welding monitoring system based on digital twin according to claim 1, characterized in that: The system further includes a model rendering module, which is specifically used for: Obtain images to be analyzed from all directions of the side seam welding equipment and welded products in the actual scene; Extracting element features from the image to be analyzed, wherein the element features include texture features; generating a rendered sticker based on the texture features; Obtaining images to be processed in all directions of the three-dimensional model; Determining an adjustment ratio of the texture feature based on the image to be analyzed and an image to be processed corresponding to the image to be analyzed; Adjusting the rendered sticker based on the adjustment ratio; Stick the adjusted rendering sticker to the corresponding position of the corresponding 3D model.

7. A power battery module side seam welding monitoring system based on digital twin according to claim 1, characterized in that: The system further includes a debugging module, which is specifically used for: Get the user's debugging information; generating a moving path of the three-dimensional model based on the debugging information; Moving the three-dimensional model based on the moving path; Performing collision detection on the moved three-dimensional model, and generating an adjustment path based on the collision information when the moved three-dimensional model collides; The three-dimensional model is adjusted based on the adjustment path, and the adjustment data is displayed.

8. The power battery module side seam welding monitoring system based on digital twin according to claim 1 is characterized in that: The report generation module is specifically used for: Obtaining a three-dimensional model corresponding to the warning information; Adjusting the three-dimensional model to the problem area corresponding to the alarm information to obtain an adjusted three-dimensional model; Capturing a display image of the adjusted three-dimensional model; generating a model link of the adjusted three-dimensional model; A welding report is generated based on the model link, the display image and the warning information.

9. A power battery module side seam welding monitoring system based on digital twin according to claim 8, characterized in that: Before adjusting the three-dimensional model to the problem area corresponding to the warning information, the method further includes: Classifying the welding data to obtain data types; Performing a first number on each of the data types; Performing a second numbering on the display area of ​​each of the three-dimensional models; The data type is associated with the corresponding display area based on the first number and the second number.

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